Corporate culture, management commitment, and HRM effect on operation performance: The mediating role of just-in-time

Abstract

The motivation of this study is to analyze the impact of corporate culture, management commitment, and Human resources management on operational performance and the mediating effect on those relationships from JIT implementation. A questionnaire-based survey was used to investigate the research questions. Data from a sample of 410 manufacturing plants were analyzed using a Structural Equation Modeling (SEM) procedure. Study findings unveil direct effect running from corporate culture, management commitment, HRM, and JIT to operational performance. Considering the indirect effect i.e. the mediating role of JIT, findings suggesting that there is partial mediation available in the estimation. On the other hand, the direct effects of corporate culture, management commitment, and HRM on JIT is positive and statistically significant. It is advocated that the effective implementation of JIT in manufacturing units can contribute to increasing operational performance side by side the presence of other key organizational attributes.

Keywords:

• just-in-time
• operational performance
• CFA
• path model
• SEM

PUBLIC INTEREST STATEMENT

Even though, the effects of JIT on operational performance have been investigated in empirical studies. However, considering the RMG industry of Bangladesh, for the first time we investigate both direct and indirect effects of JIT on operational performance. Study findings will enrich the thinking process of managers especially, those who are dealing with production management and cost controlling issues for increasing profit possibility for the organization. Furthermore, a newly set-up production plant will be able to get an informative idea relevant to how JIT can contribute to organizational performance if they plan to implement it.

Competing interests

The authors declare no competing interest.

1. Introduction

Organizational performance is a vital indicator of any organization’s success or failure. performance measures in terms of both quantitative as well as qualitative terms, and it is achieved by the efforts of individual employees and departments (Zehir et al., 2016). Moreover, the success of an organization based on its performance that how well an organization achieves its objectives (Randeree & Al Youha, 2009). Organizational performance means the effectiveness of an organization in the achievement of their desired goals (Henri, 2004). Meanwhile, organizational performance is a factor that measures how well an organization attains its desired goals (Hamon, 2004; Venkatraman & Ramanujam, 1987) Moreover, organizational performance playing a vital role in the existence of any kind of organizations such as profit-making organizations and non-profit making organizations (Abu-Jarad et al., 2010).

Operational success and growth is the outcome of collaborative effects from a number of organizational attributes including effective human resources management (Huselid & Becker, 2011; Wright et al., 2003; Wright & McMahan, 1992), hereafter HRM, corporate culture (Gebauer et al., 2010; Kotter, 2008; Yan et al., 2020), employee motivation (Dobre, 2013; Rajhans, 2012; Shahzadi et al., 2014; Yunus et al., 2020), strategic management (Chiarini & Vagnoni, 2015; Poister, 2010), employee participation (Groen et al., 2017; Hickey & Casner-Lotto, 1998; Razalli, 2020), process innovation (Al-Sa’di et al., 2017; Ju et al., 2016; Tarigan, 2018), employee development (Basuki & Khuzaini, 2020) (Mohr et al., 2012; Yee et al., 2008), management commitment (Hanafi & Fatma, 2015; Koufteros et al., 2014; Rehman et al., 2019; Shah et al., 2014), Green HRM (Mandip, 2012). Organizational capabilities (Barney, 1991; Obeidat et al., 2016) and so on. Therefore, organizations need to understand their critical attributes that are responsible for the growth and investigate their contribution on a timely basis.

Competitive pressures force manufacturers to continuously improve the provision of products and associated services desired by customers. Manufacturers have adopted lean practices such as JIT and TQM to reduce costs and improve quality. As many competitors adopted these practices, some competitive advantage was lost. Many manufacturers now have begun adopting practices that increase their ability to rapidly respond to changes in customer demand. For these, superior responsiveness has become a key to competitive advantage and maintain current performance with substantial growth.

Effective implementation of Just-In-Time, hereafter JIT, especially in the manufacturing process is critical to achieving sustainable process i.e. continuous improvement in operational performance. In empirical litterateur, a vast number of researchers observed and established the positive effects of running from JIT to performance. JIT traces its origins from the Toyota production system (TPS) (Biggart & Gargeya, 2002), from which it inherits tools and techniques, such as Kanban, cellular manufacturing, setup time reduction (or SMED), production smoothing, lot size reduction, and JIT supply ((Flynn et al., 1995; Furlan et al., 2011). It was empirically demonstrated that the application of JIT practices helps to dramatically improve operational performance by eliminating all sources of waste from production processes (Mackelprang & Nair, 2010; Shah & Ward, 2007).

JIT eliminates waste through a simple production process, organizes the smooth flow of materials, reduces set up time, and efficiently utilizes resources. JIT practice is considered as a powerful tool to reduce waste and inefficiency, speed up the production process, and delivery performance (Danese & Romano, 2011). In manufacturing companies, significant improvements in the production process are positively linked with the adaption of JIT production (Hayes, 1998). It was empirically demonstrated that the application of JIT practices help to dramatically improve operational performance by eliminating all sources of waste from the production process (Ketokivi & Schroeder, 2004; Mackelprang & Nair, 2010; Shah & Ward, 2003; Womack & Jones, 1997)

However, the skepticisms side of JIT effects also available in literature i.e. insignificant influence on operation performance see, for instance, (Abdallah et al., 2019; Dean & Snell, 1996; Nugroho, 2007; Shah & Ward, 2003). They postulated that successful implementation of JIT asked for managerial commitment, organizational efficiency, and adaptive organizational culture. Therefore, Heiko (1989), GC Kim and Takeda (1996) expressed skeptic attitudes in regards to the successful implementation of JIT in the production process, especially outside of Japanese culture.

On the other hand, effects from technical factors including corporate culture, top management commitment, effective HRM, are also expected to significantly influence the implementation of JIT and their effects on of performance measurement, their impact may be secondary to that of organizational factors (Shields & Young, 1989). In a study of (Shields, 1995), he argues that top management support for the effective implementing of JIT is crucial because these managers can focus resources, goals, and strategies on initiatives they deem worthwhile.

This study is unique in two aspects. First, with our best understanding, this is the first-ever study where JIT’s presence as mediating variable in examining the relationship between key organizational attributes i.e. corporate culture, management commitment, and HRM practices, on the operational performance of the manufacturing industry in Bangladesh, more precisely on RMG sector. Although, the effects of key organizational attributes on performance investigate but in a very negligible number. Second, this study findings not only exposed the direct effect from JIT on operational performance which extensively investigate across the world but the indirect effects yet to unleash with the presence of key factors for the organization focusing on manufacturing units in Bangladesh.

The rest of the paper is organized as follows. A brief explanation of each variable presented in Section II. Section III dealing with relevant literature review and hypothesis formulation. Model estimation and its interpretation displayed in Section IV. Finally, the conclusion from our research work presented in Section V.

2. Literature review and hypotheses

2.1. Corporate culture and operational performance

Corporate culture denotes the characteristics way of believing and behaving a group of persons have developed over time and share in common within organizations (Tarique et al. 2015). The behavior, according to Singh (2008), of the employee influence by the cultural practice possesses by the organization. Organizational culture has been identified as a mediating variable in this study. There are many terms used by different researchers to denote organizational culture. Similarly, there are many definitions of organizational culture. Organizational culture has been characterized by many authors as something to do with people and the unique quality and style of the organization (Kilmann et al., 1985), and the way things are done in the organizations (Deal (Deal & Kennedy, 1982). Sometimes, according to Deal and Kennedy (1982) organizational culture is also known as “corporate culture”. “Corporate Culture” is used to denote the more “commercialized” meaning of organizational culture.

The effect of corporate culture on performance also extensively investigated in the empirical literature and the effects of the corporate culture. First, corporate culture positively linked with organizational performance see, for example,

According to RBV theory organizational resources helps to enhance organizational performance with the help of organizational capabilities.

2.2. HRM and operational performance

The role of human resources management, hereafter HRM, extensively investigated in empirical studies focusing in multidimensional areas including employee performance (Aycan, 2001; Hassan, 2016; Purcell & Kinnie, 2007), job satisfaction (Brown et al., 2008; Chow et al., 2007; Georgellis et al., 2008; Jeet & Sayeeduzzafar, 2014; Steijn, 2002)), employees turnover (Purcell, 2003). However, a group of researchers keen to assess the influence of HRM on organizational performance, they hypothesized that HRM practices are a process of attracting, motivating, and retaining employees to ensure the survival of the organization. HRM practices, according to MacCannell (1992) Pfeffer and Jeffrey (1998), like performance appraisal, employee training, and development increase employee participation in the organization and eventually increase operational performance. Furthermore, the successful organization considers HRM is one of the critical elements for their survival.

The relationship between HRM practices and operational performance, in accordance to existing literature, is positive and ample evidence is available to see for an instance, Punnakitikashem (2014), Teclemichael Tessema and Soeters (2006), Boselie et al. (2009), Combs et al. (2006), Van De Voorde et al. (2012), Jensen et al. (2013), Takeuchi et al. (2007), and Tregaskis et al. (2013). The role of HRM in operation performance traced by researchers in different ways such as performance enhancers (Delaney & Huselid, 1996). In the study of Cristiani and Peiró (2019). They established effective and collaborative HRM practices that significantly reduce employee turnover and increase operation and financial performance. According to (Boselie et al., 2005), HRM aggregated outcomes, such as labor productivity, turnover, and employee satisfaction, contribute to improving internal organizational performance, such as productivity and quality, and these improvements, in turn, positively impact the financial performance of firms. Productivity and quality are positively associated with financial performance (Cooke, 2018; Crook et al., 2011). In light of these findings, we propose:

2.3. Management commitment and operational performance

Management commitment is traditionally defined as a strong belief in and acceptance of the organization’s goals and values, a willingness to exert considerable effort on behalf of the organization, and a definite desire to maintain organizational membership” (Basu et al., 2002; Roast & Silva-Rojas, 2007). In other words, organizational commitment is the extent and degree of confident regarding the employee’s connection and belongings to the organization (Joo & Shim, 2010; Mosadeghrad & Ferdosi, 2013)

Management commitment augments organizational performance both in the short run and long-run. In the study of Ataseven et al. (2013), they postulated that management commitment influences performance in three distinct directions that are human capital, organizational capital, and social capital. Human capital referees to knowledge, experience, skills, and capabilities to perform in the organization by adopting a new process. Higher managerial commitment, according to Alhaqbani et al. (2016), provides a governing mechanism in the organization and allows to foster organization capacity through enhancing employees’ capabilities. They also postulated that top management commitment is the key to achieve long term sustainable performance in the organization.

The positive association between management commitment and operational performance investigated in the empirical literature and established see for example, Rehman et al. (2019), Nazir and Islam (2017), Punnakitikashem (2014), Sharma et al. (2016), and Babakus et al. (2003). They postulated that management commitment influence on operational performance in three different channel that is human capital, organizational capital, and social capital. Human capital, according to (Ataseven et al., 2013), includes knowledge, skills, and attitudes residing by individuals. Human capital play a critical role in the time of implementation of the innovative production process. Organizational capital according to Subramaniam and Youndt (2005), refers to institutional knowledge and experience possessed by the organization. Organizational capital is one of the crucial factors that drive the success of any initiative or implementation in Organizations. When the lean project is implemented; it is required to standardize the process and to have documentation (Ataseven et al., 2013). Social capital includes integration of tacit and explicit knowledge to enhance the employee capabilities through communications, interactions, and collaborations. Knowledge dissemination occurs when employees interacted with each other through various forms in their networks. Knowledge dissemination in the organization can be improved with appropriate social capital. The use of information could potentially improve products and processes and enhances the understanding of patients’ needs (Ataseven et al., 2013; Bendoly et al., 2007).

2.4. JIT and operational performance

Just-in-time (JIT) practices are very useful to improve operational performance. These practices, which represent the core of Lean management methodology, were firstly developed in Toyota, where the production is highly repetitive, and for many years researchers have thought that this methodology could be applied in contexts characterized by repetitive manufacturing systems only.

Positive thought available in a number of empirical studies see, for instance, (Ahmad et al., 2004; Bortolotti et al., 2013; Fullerton et al., 2003; Green et al., 2019; Holweg, 2007; Inman et al., 2011; Klingenberg et al., 2013; Mackelprang & Nair, 2010; Mas’ Udin & Kamara, 2018; Motwani, 2003; Phan et al., 2019; Shah & Ward, 2003; Ward & Zhou, 2006; Zelbst et al., 2010) (Balakrishnan et al., 1996; Chong et al., 2001; Droge & Germain, 2000; Fullerton & McWatters, 2001)

They postulated that JIT implementation in the production process assists in increasing efficiency in managing the entire process which leads to greater productivity with higher performance compared to past performance without JIT implementation. Further, according to Manoochehri (1984), Brown and Mitchell (1991), and Womack and Jones (1997), effective implementation of JIT minimize operational cost through reducing business cycle time, increasing flexibility in delivery and procurement process, and enduring effective inventory management.

Mackelprang and Nair (2010) conducted empirical studies about the impact of JIT practices on operational performance and concluded that JIT improves most performance dimensions, in particular manufacturing costs, inventory turnover, cycle time, on-time delivery, fast delivery, volume flexibility and mix flexibility. The contrasting view regarding JIT and operational performance also available in empirical literature see for example, (Dean & Snell, 1996)

3. Research problem

JIT and operational performance are extensively discussed topics in empirical Literature especially focusing on the manufacturing plant and the benefits of JIT implementation also established. However, empirical literature produced a piece of negligible evidence concentrating on the relationship between JIT and the operational performance of manufacturing units in Bangladesh. Considering the contribution to national income, the RMG industry emerged as one of the thrust sectors and their role is critically acknowledged. And their growth is also phenomenal, however, a number of manufacturing plants going shutdown due to incapacity for producing a substantial profit. With this study, we tried to figure out the role of JIT implementation on organizational performance, and therefore, we purposively select those production units who are using the JIT concept in their production process. These findings will enlighten the production manager in case of understanding the relationship i.e. how JIT contributes to the organization precisely the performance augment role played by JIT with the presence of other key organizational attributes. The following Figure 1 represents the causal relations and the possible tested hypothesis see, Table 1, which will be analyzed through Path model estimation.

Figure 1. Research framework (Author construction).

4. Research methodology and data collection

4.1. Questionnaire development

A structured questionnaire was developed to collect data. The questionnaire comprises six parts, the first part is about the basic information of surveyed companies and respondents, the second part is about the corporate culture situation which is measured by a set of Likert question which is adopted from empirical studies see, for an instance (), the third part is about the Management commitment situation, which is measured by a set of indicators. The latent construct extracted from existing empirical studies see for an instance ().the fourth part dealing with the talent construct measuring the HRM practices in the organization. All the later contracts are exported from past studies. the fifth part is about the operations performance, which is measured by a set of latent construct adapted from empirical literature by following Baird et al. (2011), Kaynak (2003), and Chen (2015) and finally the six-part has about measured the presence of JIT in the production process. The latent constructs are adopted.

Before formally collecting data, we first contacted several local manufacturing firms’ managers around the district of the author’s institute, and asked them to participate in a pre-test of the questionnaire and then consulted them about the revision of the questionnaire. Based on the feedback from the pilot survey, we then clarified the language expression of some questions, made all items easy to understand, and be precisely answered.

4.2. Sampling and data collection

This study applies purposive sampling techniques to obtain data from those Ready-made garments who are exporting goods at least over the past 5 years. The list of respondents are selected from available data from BGMEA, a list of 510 RMG production units are selected based on their export performance that is duration. Data were collected during the period of 17 February 2020, to 20 March 2020. Data were collected from three export processing zone in Bangladesh namely, the Dhaka export processing zone, Camilla export processing zone, and Chittagong export processing Zone. Obtaining pertinent data, managerial level personnel were selected and approach for their response. Out of 510 prospective responses, however, 410 useable responses were collected. The response rate was 80.39%. The demographic profiles of respondents exhibited in Table 2.

Table 1. List of the proposed hypothesis

Hypothesis	Description	Path	JIT presence
${\mathrm{H}}_1:$	Corporate Culture has a significant influence on organizational performance.	cc→OP	NA
${\mathrm{H}}_2:$	The association between corporate culture and operational performance positively mediate by Just-in-Time	CC→JIT→OP	Mediating
${\mathrm{H}}_3:$	HRM practices positively influence on operational performance	HRM→OP
${\mathrm{H}}_4:$	The association between Human resource Management and operational performance positively mediate by Just-in-Time	HRM→JIT→OP	Mediating
${\mathrm{H}}_5:$	Management commitment positively influence on operational performance	MC→OP
${\mathrm{H}}_6:$	The association between management commitment and operational performance positively mediate by Just-in-Time	MC→JIT→OP	Mediating
${\mathrm{H}}_7:$	Corporate culture influence on JIT implementation	CC→JIT
${\mathrm{H}}_8:$	Management commitment influence on JIT implementation	MC→JIT
${\mathrm{H}}_9:$	HRM practices influence on JIT implementation	HRM→JIT
${\mathrm{H}}_{10}:$	JIT positively influence on operational performance	JIT→OP

Table 2. Demographic profile

Business age (Years)	n	%	Export experience	n	%
less than 5	45	11%	Less than 5	45	11%
between 5–10	125	30%	between 5–10	125	30%
between 10–15	170	41%	between 10–15	170	41%
more than 20	70	17%	More than 15	70	17%
Firm size			Respondents education
less than 25	128	31%	HSC	65	16%
between 50–75	144	35%	Graduate	73	18%
between 75–100	78	19%	Post graduate	259	63%
more than 100	60	15%	PhD	14	3%
Respondent age (year)
between 25–30	89	22%
between 30–35	95	23%
between 35–40	155	38%
more than 40	71	17%

Source: Author compilation

4.3. Measures

4.3.1. Organizational performance

There is no consistent opinion on the measures of production operations performance. Usually, cost, quality, productivity, inventory, customer satisfaction, and delivery ability, etc., are often taken as measures of production operations performance. Based on other literature, the following five measures can be used as operations performance. The results of confarmitory factor anaysis exhited in Table 3.

On-time delivery. It is obvious that implementing JIT in the organization can improve on-time delivery performance, since the name of JIT, i.e., just-in-time, has reflected the idea of on-time delivery (Ohno, 1982). In literature, many authors used on-time delivery or similar measures to examine the delivery performance of the implementation of JIT (Cua et al., 2001; Davenport & Glaser, 2002; Matsui, 2007; Yunis et al., 2013)

Labor productivity. Generally speaking, implementing JIT can improve productivity, since JIT emphasizes the idea of waste reduction high quality, both of them can increase the output of the production system (RE White et al., 1999b; Zelbst et al., 2010).

Inventory level. Inventory level is a very important measure for JIT, since implementing JIT can reduce inventory, especially, JIT emphasizes the concept of zero inventory, also, the higher the quality, the lower the scrape inventory. (Alcaraz et al., 2014; García et al., 2014)).

• Cost efficiency. Since JIT can reduce all kinds of wastes in production processes and quality loss costs, such that, JIT can reduce costs. Therefore, it is reasonable to use cost efficiency as a measure for JIT (Cua et al., 2001; García et al., 2014; Matsui, 2007).

• Customer satisfaction. JIT is the genesis of time-based competition (Fullerton et al., 2003), implementation of JIT can obtain effective customer response. Also, the customer focus concept of TQM (Flynn et al., 1995) means that the implementation of TQM can obtain high customer satisfaction. Therefore, customer satisfaction can be taken as a measure of JIT and TQM performance.

4.3.2. Management commitment

Management commitment influence on the operational performance of the organization is a fact, it is arguable that without management consideration any strategy might not work with a full swing (). Therefore, effective implementation of the plan towards increasing performance, the presence of top management commitment is inevitable (Oakland, 2014; Zairi, 1995).

Management commitment is one of the important factors in the use and implementation of performance measurement systems by public sector organizations. Management commitment is an emotional attachment, and a form of loyalty, by people who are members of the organization, and who devote their attention, ideas, and responsibilities to achieve the missions, values, and goals of their organization (Primarisanti & Akbar, 2013). The latent construct and CFA analysis results reported in Table 4.

4.3.3. HRM practices

The importance of effective HRM practices in the organization is extensively investigated considering both the service and manufacturing industries. Therefore, in the empirical literature, a number of latent constructs were used for getting feedback regarding HRM practices in the organization and assess its effect on performance. in this study, We used 5 commonly used items that are measured on a Likert-type scale ranging from 1 is “very strongly disagree” to ‘5 is very strongly agreed, by following existing literature.

The latent constructs include, The “recruitment and selection” (RS) comprises harmonized and term conditions, single status for all staff, internal promotion norm, employment test criteria, merit element in selection, and multi-skilling and experience. The second “manpower planning” (MP) comprises formal manpower planning, work culture, career planning, and involvement of all departments. The third attribute “job design” (JD) comprises flexible job descriptions, development of a learning organization, cross-cultural job design, and team working. The fourth attribute “training and development” (TD) comprises of need-based training and development criteria, formal system induction, learning organization, formal training, and development. The fifth attribute “quality circle” (QC) comprises staff involvement in objective setting, production/service staff responsible for their service, employees’ involvement in quality circles, and regular use of attitudes surveys. The items were measured using a 5-point Likert scale. The measurement variables and the results of CFA reported in Table 5.

4.3.4. Corporate culture

Corporate culture in empirical studies measured by using several items and define with diversified aspects. Corporate culture, according to (Kilmann et al., 1985), dealing with people’s involvement, unique quality, management style, and the way to perform by the organization (Deal and Kennedy). In this study we adopted the definition from (Hofstede, 1980), he advocated that corporate culture is a set of activities including shared beliefs, values, and practices that distinguish one organization from another.

For the measurement of corporate culture, scholars/theorists have put forward several measures of corporate culture like Hofstede (1980), Wallach (1983), Cameron and Quinn (1999), and Kotter (2008). However, the questionnaire used in the present study is adopted from Ogbonna and Harris (2000) and. The questionnaire includes 5 items and it is validated in cross-cultural researches. The measurement variables and the results of CFA reported in Table 6.

4.3.5. Just-in-time

Assessing the presence and effective implementation of JIT in the organization measured by using different indicators such as Sakakibara et al (1993) defined sixteen elements of JIT. Cua et al. (2001) defined five elements. Matsui (2007) defined nine elements, Mackelprang and Nair (2010) summarized ten elements and Chen (2015) defined 10 items in respective studies. Therefore, it is utterly impossible to stand-up with any consensus for latent constructs for measuring JIT in the operation. However, aligning with literature, in this study we consider five measures for testing the role in the model. These are given below.

· Uniform workloads. This element is also called a level schedule, smoothing and mixed production (Hallihan et al., 1997)It requires materials to go through the production line in a pattern of uniform loads in order to reduce the variance of variety and quantity over time ((CM White et al., 1999a)). Uniform workloads can reduce the waste of resource, and increase the utilization of capacity

· Standardized operations. In order to reduce motion waste, JIT production emphasizes operations should be standardized (in practice, some industrial engineering methods, e,g. time study and motion study, are used to set standardized time and operation for each worker). It is often viewed as an infrastructure work of JIT and lean production (Jacobs et al., 2014; Monden, 1983; Womack & Jones, 1997).

Small lot size. In order to quickly respond to customer demand, shorten the lead time, and

Work-in-process inventory, JIT production emphasizes using a small lot size to produce products. This element was also cited by some authors (Danese et al., 2012; Mackelprang & Nair, 2010); (Boulter et al., 2013; Chen, 2015; Chen & Tan, 2013)

Kanban system. In JIT production system, according to (Sugimori et al., 1977), Kanban is a signaling device (usually is a card) used to regulate material flows, it can be used in shop flow to control production line (called production Kanban) or used to control supplying of materials from suppliers (called supplying Kanban). It is also an often mentioned element of JIT in academia (Chen, 2015; Chen & Tan, 2013; Kundu et al., 2019; Rahman et al., 2013; Sharma & Singla, 2019; CM White et al., 1999a)

Setup time reduction. This is an often mentioned element of JIT in the literature ((Bond et al., 2020; Chen & Tan, 2013; Fullerton et al., 2003; Shah & Ward, 2003). Setup time reduction is also called quick changeover, its role is to reduce the waste of changing from producing one product to other products.

The measurement variables and the results of CFA reported in Table 7.

4.4. Measures scores and normal distribution test

The section dealing with descriptive and normal distribution test of selected latent construct. The result reported in Table 2. The average scores of measures range from a minimum of 3.39 to a maximum of 4.20, indicating that an overall positive response to the constructs. This means that all the items of CC, MC, HRM, JIT, and OP, as well as the indicators of production, have obtained a positive effect in surveyed firms averagely. Because the maximum likelihood estimation procedures were used in this study, the normality assumption must be not severely violated (Curran et al., 1996). Following the guidelines of server nonnormality (i.e., Skewness>3; Kurtosis>10) proposed by (Kline, 2005), the values of Skewness and Kurtosis reported in Table 2 & Table 8 show that the sample can be confirmed to satisfy the assumption of the normal distribution, it can be further analyzed.

5. Model estimation and findings

5.1. Scale measurement, reliability, and validity

The corporate culture was measured with five (05) scale items obtained from. Human resources management measure with five item-scale obtained from Mira et al. (2019). Management commitment measured with five item-scale obtained from Alharthi et al. (2019) Albadry (2016) and Operational performance measured with five item-scaled, obtained from Baird et al. (2011); Kaynak (2003). The moderator variable that is Just-in-time measured with five item-scale, obtained from Danese et al. (2012); Bortolotti et al. (2013). All constructs were rated on a five-point Likers scale ranging from “1 = “Strongly Disagree, to “5 = Strongly Agree”. To ensure the face validity of scales, a pilot study was conducted with 50 questionnaires, which confirms that no changes are required because of the results. Table 2 & Table 9 presents the details of all items

The construct validity was also tested by using the convergent and discriminant validity. composite reliability (CR) and average variance extracted (AVE) techniques were used to check the convergent validity, whereas, Fornell and Larcker (1981) method were used to check the discriminant validity. The convergent validity and discriminant validity were confirmed as the values of CR and AVE presented in Table 2 & Table 9 were greater than the cutoff levels, i.e. (CR > 0.70), and (AVE > 0.50) (CR > AVE). Referring to the results exhibited in Table 2 & Table 9it is confirmed that the value of CR and AVE was greater than the cut-off level i.e., CR>0.70, AVE>0.50.

Furthermore, following Fornell and Larcker (1981) proposed a way of confirming validity, i.e., the comparison between the correlation of coefficient of each contract and Square root of AVE. The results of the discriminant validity reported in Table 4/ Table 10. The construct correlation coefficients are less than the square root of AVE. Discriminant validity refers to a situation in which we see that two indicators are statistically different. Moreover, discriminant validity demonstrates the level to which a variable in the actual term is dissimilar from another variable based on empirical gauges (Hair Jr et al. 2014).

Table 3. Measures of operational performance

Operational performance	Reference	CFA
. Improved product/service quality.	Baird et al. (2011); Kaynak (2003); Chen (2015), (Cua et al., 2001; Davenport & Glaser, 2002; Matsui, 2007; Yunis et al., 2013)	($X_5^2=15.10$, NFI = 0.958, RFI = 0.874, GFI = 0.974, IFI = 0.963 and CFI = 0.963).
. Increased productivity.
. Reduced costs of defects and rework.
. A reduced delivery lead time of finished products/services to customers.
. Reduced customer complaints

Table 4. Measures of management commitment

Management commitment		CFA
The positive attitude of management to solve problems concerned with employees	Alharthi et al. (2019) Albadry (2016);Pollanen et al. (2017) Ahyaruddin and Akbar (2016), Cavalluzzo and Ittner (2004) Nurkhamid (2008)	($X_4^2=4.62$, NFI = 0.989 RFI = 0.966, GFI = 0.974, IFI = 0.993 and CFI = 0.993.
Top management support for implementing quality-related programs
Top management supports middle management for quality performances
Tower level managers/supervisors conduct the daily meeting before starting the work
Senior managers attend JIT, Lean and quality-related seminars and workshops

considering all the results reported in Tables 2 and Table 10 we can conclusively confirm the measurement scale reliability and validity following proposed guidelines by Fornell and Larcker (1981).

Table 5. Measures of HRM practices

Human Resources Management		CFA
Feedback is given properly to the employees where necessary	Sparrow et al. (2016); (Becker & Gerhart, 1996) (Delery & Roumpi, 2017) (Sparrow et al., 2016; Collings et al., 2018; Delery & Roumpi, 2017; Oakland, 2014)	($X_5^2=29.83$, NFI = 0.970 RFI = 0.975, GFI = 0.974, IFI = 0.975 and CFI = 0.975).
Management gives careful attention to the recruitment of employees
Harmonized employment and promotion related terms and conditions apply for all
Strong communication and coordination exist among management and employees
Employees work as a team rather than an individual in our company

Table 6. Measures of corporate culture

Corporate Culture	Reference	CFA
Employees are supportive if asked to work longer hours	Baird et al. (2011), Lee and Yu (2004), Sofi and Devanadhen (2015),
Priority on organizational interest over personal interest
Management participates with the employees in the social gathering
Mid-level management participation is encouraged in the decision-making process
Employees are committed to work

Table 7. Measures of JIT

Just in Time
We usually complete our daily schedule as planned.	Danese et al. (2012); Bortolotti et al. (2013)	($X_5^2=29.83$, NFI = 0.970 RFI = 0.975, GFI = 0.974, IFI = 0.975 and CFI = 0.975).
The layout of our shop floor facilitates low inventories and fast throughput.
We use a Kanban pull system for production control.
We have low setup times of equipment in our plant.
We emphasize small lot sizes, to increase manufacturing flexibility.

Table 8. Mean, standard deviation, skewness, and kurtosis of latent constructs

	level	Mean	Standard deviaton	Skewness	Kurtosis
Corporate culture	CC1	3.72	1.230	−.733	−.402
	CC2	3.55	1.124	−.439	−.624
	CC3	3.39	1.246	−.522	−.655
	CC4	3.65	1.207	−.769	−.272
	CC5	3.84	1.109	−.632	−.466
Management commitment	MC1	3.56	1.284	−.561	−.768
	MC2	3.83	1.263	−.902	−.238
	MC3	3.78	1.234	−.780	−.392
	MC4	3.83	1.187	−.845	−.208
	MC5	3.74	1.324	−.842	−.469
Human Resources Management	HRM1	3.96	1.095	−1.059	.507
	HRM2	3.67	1.296	−.797	−.463
	HRM3	3.60	1.262	−.692	−.561
	HRM4	3.87	1.115	−.685	−.429
	HRM5	3.55	1.285	−.545	−.787
Just-in-time	JIT1	4.20	1.127	−1.511	1.572
	JIT2	3.71	1.379	−.744	−.751
	JIT3	4.12	1.172	−1.299	.822
	JIT4	3.55	1.490	−.544	−1.157
	JIT5	3.73	1.357	−.730	−.732
Operational Performance	OP1	3.72	1.242	−.804	−.327
	OP2	3.66	1.215	−.631	−.541
	OP3	3.72	1.174	−.714	−.368
	OP4	3.62	1.305	−0.678	−.637
	OP5	3.4572	1.21419	−0.535	−.630

Table 9. Construct details and validity results

		Factor loading	Cronbach’s alpha	kmo	CR	AVE	SAVE
Corporate culture	CC1	0.802	0.868	0.789	0.915	0.686	0.618
	CC2	0.717
	CC3	0.889
	CC4	0.883
	CC5	0.842
Management commitment	MC1	0.877	0.872	0.792	0.936	0.746	0.636
	MC2	0.857
	MC3	0.910
	MC4	0.845
	MC5	0.829
Human Resources Management	HRM1	0.782	0.896	0.811	0.928	0.721	0.613
	HRM2	0.829
	HRM3	0.879
	HRM4	0.880
	HRM5	0.874
Just-in-time	JIT1	0.801	0.815	0.752	0.923	0.707	0.686
	JIT2	0.876
	JIT3	0.809
	JIT4	0.843
	JIT5	0.873
Operational Performance	OP1	0.842	0.913	0.798	0.928	0.748	0.629
	OP2	0.904
	OP3	0.864
	OP4	0.851
	OP5	0.786

Note Composite reliability (CR), average variance extracted (AVE) and average shared squared variance (ASV).

Table 10. Discriminant validity

	Human resources management	Just-in-time	Corporate Culture	Management Commitment	Operational performance
Human resources management	0.894
Just-in-time	0.318	0.841
Corporate Culture	0.489	0.383	0.828
Management Commitment	0.281	0.431	0.125	0.864
Operational performance	0.362	0.204	0.450	0.019	0.928

5.2. Measurement model assessment

The model’s overall goodness of fit was evaluated using the various model-fit measures recommended by Hair et al. (1998); that is χ2/d.f., the normalized fit index (NFI), the adjusted goodness of fit index (AGFI), the comparative fit index (CFI), the root mean square error of approximation (RMSEA) and the root mean square residual (RMR). The results of the model fit index exhibited in Table 4/ Table 11. Based on a proposed standard by Browne and Gudeck (1992), Hu and Bentler (1999) as well as J Kim and Forsythe (2010)and J Kim and Forsythe (2010), this is an acceptable model fit. and it convincingly supports the validity and reliability Table 4 lists the observed data values along with the recommended cut-off values

5.3. Structural equation model (SEM) estimation

The following section deals with model estimation with the path model (see, Figure 2). The extracted results of direct effects running from independent variables to dependent variable exhibited in Table 5/ Table 12. Study findings revealed positive effects running from corporate culture (a coefficient of 0.133), management commitment (a coefficient of 1.795), human resources management (a coefficient of 0.165) and Just in Time (a coefficient of 0.335) to operational performance. It is mentioned here that all the path coefficients are statistically significant at a 1% level. Considering the path coefficient and its associate probability, it is convincingly established that the null hypothesis 1, 5, 6, 7 are accepted, which implies that there is a positive association between corporate culture, management commitment, human resources management, Just in time and operational performance.

Furthermore, referring to the direct effects towards Just-in-Time from corporate culture (a coefficient of 0.122), management commitment (a coefficient of 0.684) all the coefficients are statistically significant at a 1% level. But the effect running from and human resources management (a coefficient of 0.303) is not statistically significant. These findings suggesting that the hull hypothesis of 2 and 3 is accepted, which implies that Just-in-Time practices are positively influenced by corporate culture and management commitment but the influence from human resources management on Just-in-time is insignificant

The results of independent variables effects through just-in-time on operational performance exhibited in Table 13. The mediating role of Just-in-time observed statistically significant at a 1% level. These findings suggesting that corporate culture, management commitment, and human resources man agents have indirect effects on operational performance through Just-in-time. Furthermore, the effects implementation of just-in-time also significantly influenced by corporate culture, management commitment, and human resources management.

Table 11. Fit model index (CFA)

Fit indices	Recommended value	Measurement model
χ2/d.f.	≤ 3.00	2.04
NFI	≥ 0.90	0.974
CFI	≥ 0.90	0.945
AGFI	≥ 0.80	0.910
RMR	≤ 0.05	0.035
RMSFA	≤0.10	0.087

Table 12. Direct effects of the construct

Hypothesis	Exogenous		Endogenous	Std. Estimation	C.R	remarks
01	Corporate culture	→	Operational performance	0.133^a	4.166	Support
02	Corporate culture	→	Just in time	0.112 ^a	8.901	Support
03	Management commitment	→	Just in time	0.684 ^a	10.722	Support
04	Human resources management	→	Just in time	0.303 ^a	3.982
05	Management commitment	→	Operational performance	1.795 ^a	3.406	Support
06	Human resources management	→	Operational performance	0.165 ^a	4.206	Support
07	Just in time	→	Operational performance	0.335 ^a	3.107	Support

The superscript “a” indicates level of significance at 1%.

Table 13. Indirect effects of contract

Hypothesis	Exogenous	Mediating variable	Endogenous	Indirect effect	Direct effect
01	Corporate culture (1)	Just in time (2)	Operational performance (3)	1→2: 0.122 ^a 2→3:0.039 ^a	1→3 0.133 ^a
05	Management commitment (1)	Just in time (2)	Operational performance (3)	1→2:0.684^a 2→3:0.151 ^a	1→3 1.795 ^a
06	Human resources management (1)	Just in time (2)	Operational performance (3)	1→2:0.303 ^a 2→3:0.130 ^a	1→3 0.165 ^a

the superscript “a” indicates level of significance at 1%.

Table 14 exhibits that the fitness indexes of the model achieved the required level after the path model has been conducted. Considering the extracted fit index and recommended fit index, it is apparent that all the extracted fit index confirm estimated model validity and reliability.

Figure 2. Results of the proposed model of Management Commitment, Corporate culture, HRM on performance through JIT implementation.

Table 14. Theoretical and observed fit index

Fit indices	Recommended value	The value extracted from Structured equation
χ2/d.f.	≤ 3.00	2.04
NFI	≥ 0.90	0.974
CFI	≥ 0.90	0.945
AGFI	≥ 0.80	0.910
RMR	≤ 0.05	0.035
RMSFA	≤0.10	0.087

6. Discussion and implication

The motivation of the study is to investigate the mediator role of Just in time inventory process on the operational performance of readymade garments in Bangladesh. To get relevant information from respondents, a sample of 510 production units was selected and a set of the structure of the questionnaire was sent to concern personnel for expressing their views. Five points Likert’s scale was used with three independent variables namely Corporate culture, Human resources management, and Management commitment along with one dependent variable measured by operational performance. Most importantly the presence of Just in time appears in the equation as mediator. The summary of the study findings are given below:

First, referring to the results of confirmatory factor analysis, especially the model fit index. It ascertains the model reliability and validity since all the model fit index value is at par considering the recommended cut-off value. These findings suggesting that due to internal consistency and reliability, this model can be used for further investigation

7. The effects of corporate culture on operational performance with JIT as a mediator

Referring to H1, the study established the effects of running from corporate culture to operational performance are positive and statistically significant in the RMG sector. These findings in the line with (Baird et al., 2011; Bashar & Hasin, 2019; Basuki & Khuzaini, 2020; Fattah & Twigg, 2017; Guo et al., 2016; Lee & Yu, 2004; Mokhtar & Yusof, 2010; Phan et al., 2019; Santos et al., 2019; Zhao et al., 2018). In the study ofLee and Yu (2004), they postulated that Organizational culture has been linked to organizational commitment and is perceived to be a central determinant of overall organizational efficacy. Corporate culture is a set of interrelated organization and managerial activities including commitment, consistency, involvement, and adaptability. According to (Brooks, 2006), “the great organizational behavior can facilitate the corporations to have the efficient management mechanism”. Organizational culture is closely interrelated with the rest of the functions in the corporation and which has a great impact on all the business activities. Therefore, well managed and appreciated corporate culture not only accelerate the operational performance but also augment the process of organizational efficiency.

Considering H2, the study finding unveiled the positive effects running from corporate culture through JIT on organizational performance which is statistically significant. This finding advocating that the mediating role of JIT on operational performance is partly due to the direct effect from the corporate culture on operational performance is positively associated. So, one can assume here that is the effective implementation of JIT can contribute to operational performance enhancement through adding value in the organization. Cooperate culture directly influences operational performance due to the inherent properties to induce employees’ behaviors, it is supported by the existing empirical literature (Albarracín & de Lema, 2011; Hofstede & Bond, 1988; Martins & Terblanche, 2003)

8. The effects of management commitment on operational performance with JIT as a mediator

Referring to Hypothesis () which is exhibiting the direct effect running from management commitment to operational performance. Study findings found that there is a positive association (a coefficient of 1.795) and the coefficient is statistically significant at a 1% level. This finding suggesting that a 1% improvement in management commitment can accelerate operational performance by 1.795%. findings consistent with the work of Mokhtar and Yusof (2010), Baird et al. (2011), El-Kassar and Singh (2019), and Majid et al. (2019). Top management commitment plays an essential role in allocating resources, building capabilities, and helping the firm gain a competitive advantage (Chadwick et al., 2015; Sirmon et al., 2007). The knowledge and beliefs of top management influence the implementation of technologies such as large scale data throughout the organization (Chatterjee et al., 2002).

Furthermore, the indirect effect also observes from management commitment to operational performance in the presence of JIT as mediating variables. Study finding unveiled partial mediation from JIT with positive appreciation (a coefficient of 0.151). it is implying that effecting implementation of JIT can causes operational performance enhancement by 0.151 in addition to management commitment effects on operational performance.

9. The effects of HRM on operational performance with JIT as a mediator

Referring to the results of direct and indirect effects running from HRM to operational performance. Study findings produce evidence in favor of the proposed hypothesis that positive associations are established in both cases. Effective HRM practices induce operational performance through employee motivation and performance enhancement. These study findings lie with Mira et al. (2019), Bondarouk et al. (2016), Jiang et al. (2012), Ogbonnaya and Valizade (2018), and Taticchi et al. (2010). Proper human resource management practices are considered another element that firms employ to face the technological challenges of effective JIT implementation. Such practices refer to hiring and retaining employees with innovative capabilities and skills and managing these resources to achieve competitive advantages (Sirmon & Hitt, 2003). Moreover, higher firm performance is positively related to the deployment of employees’ skills and talents through such HR practices (Chrisman et al., 2003).

Further positive evidence also observed with the presence of JIT as a mediating variable in the model. The study finding confirmed the partial mediation role played by JIT.

10. Practical implications

First, our outcomes advise managers that decisions on JIT production and JIT supply implementation should differ according to the performance companies intend to improve. In particular, when efficiency is the priority, companies should direct their efforts on JIT production. Instead, when they aim to improve delivery, they should invest in both JIT production and JIT supply.

Second, A JIT practice has a high breadth impact when multiple performance outcomes are significantly improved. The depth impact of individual JIT practices is captured in terms of the magnitude of the significant relationships between individual JIT practices and performance outcomes. In a resource-constrained context, as is the case in most real business situations, managers can evaluate their implementation options based on the overall impact (breadth and depth) of a JIT practice on performance. In this regard, the impact factors can act as a guide for the implementation of those practices that will yield the greatest impact.

11. Conclusion, limitations, and further research

Despite the limitations, the study findings provided a theoretical and empirical test on the assumption in the literature that is corporate culture, management commitment, and HRM practices on organizational performance through the presence of Just-in-Time. It is observable, apart from direct relationship, partial indirect effects running from corporate culture, management commitment, HRM to operational performance through JIT. Study findings suggest that effective implementation of JIT in the production process can contribute substantially to the increase of organizational capacity and augment the earning prospect, eventually. JIT performed a number of critical roles like wipe off waste through a simple production process, organizes the smooth flow of materials, reduce setup time, and efficiently utilizes resources. Just-in-time (JIT) practice is considered as a powerful tool to reduce waste and inefficiency, speed up the production process and delivery performance. JIT implementation, according to Ward and Zhou (2006) in the industry produces a high-quality product based on customer demand. These study findings extend the existing belief that effective implementation could augment operational performance. Furthermore, the contribution from corporate culture, management commitment, and effective HRM on the enhancement of operational performance can be maximized with better performance. it is also established a strong relationship among corporate culture, management commitment, HRM and JIT and that practice jointly impact operational performance.

This study has two main limitations. First, the data was collected using a questionnaire at a single point in time. As a result, we could not rule out the possibility of spurious correlations between the dependent and independent variables and thus, the study does not allow for dynamic causal inferences (Cavanaugh & Noe, 1999). Future research would benefit from employing longitudinal data. Second, in aggregating the data of senior managers, middle managers, and other employees, the sample sizes used were rather small. Future research should aim for larger sample sizes for this purpose.

Acknowledgements

The author appreciates the two anonymous reviewers for their constructive suggestions in improving the quality of this paper.

Additional information

Funding

This research is funded by The institute of Advanced Research, United International University, Bangladesh [UIU/IAR/02/2019-20/BE/01].

Notes on contributors

Salma Karim

Professor Dr. Salma Karim, currently working in the School of Business and Economics of United International University (UIU), Dhaka Bangladesh. She possesses an excellent teaching experience of almost thirty two years. Her basic discipline is accounting, with more focus on Management Accounting. She did her PhD from University of Dhaka in quality management topics like Just In Time production practices. Recently in addition to working on JIT, she is also doing research on finance related topics like FDI, Interest rate, exchange rate, monetary.

M. D. Qamruzzaman

Dr. M. D. Qamruzzaman is an associate professor of finance and Accounting at the School of Business and Economics at United International University, Bangladesh where he teaches courses at both the graduate and undergraduate levels. His current research focuses on financial innovation, SMEs financing, Renewable energy, financial volatility, business excellence models and TQM practices, and foreign direct investment. He holds a PhD in Industrial economic from Wuhan University of Technology (WHUT), China.